Research Data Management is essential for responsible research and should be introduced when starting a new project or joining a new lab. Managing data across a project and/ or a team allows for accurate communication about that project.
This session will review the important steps for onboarding new employees/trainees to a lab or new projects. The key take-away from this session will be how to incorporate these steps within your individual project or lab environment.
Publishing research data within a trusted repository helps you comply with funder and journal data sharing policies, supports the discovery of and access to data, and can result in more visibility and higher impact for research projects. These shared datasets can be cited and referenced by yourself and by other researchers.
This seminar will provide an overview of sharing data in a repository and how to structure a data citation.
Dropbox is a file hosting service that offers cloud storage, file synchronization, version control, online editing, and more. Entire Labs can promote collaboration via Dropbox which provides a platform for accessing shared data without taking up valuable space on your computers.
This seminar will explore how you can effectively utilize Dropbox for managing your research files and entire research project.
Note: we will focus on Dropbox for Business which is available for the Harvard research community.
To ensure that you understand your own data and to enable others to find, use and properly cite your data, it helps to create README files with ‘documentation’ or ‘metadata’ about the datasets you create.
This session will explore the critical role documentation plays in data management and how you can ensure good documentation throughout your research.
Define common types of documentation
Understand why documenting your research is important...
File naming, when done in a well-organized fashion, can contribute to project documentation, workflow organization, and sharing. Establishing naming conventions for your files and using them consistently will ensure maximum access to your data and records.
This seminar will review how file naming conventions will save you time by keeping your work organized and understandable.
Understand why naming conventions are essential for data management
Data organization refers to the method of classifying and organizing data sets to make them more useful. Once you create, gather, or start manipulating data and files, they can quickly become disorganized. To save time and prevent errors later on, you and your team should decide how you will structure folders and organize your files.
This seminar will review best practices for when it comes to organizing you research project, data, and files effectively.
Many key granting organizations, like NSF, NIH, NEH and more, now require submitters to include a Data Management Plan (DMP) as part of their application. In short, these plans outline the best practices in data management that you will apply throughout the course of your grant. By creating a data management plan for your data at the beginning of the project, you save time and effort later on.
This session will provide an overview of the components of typical data management plans.
Data is a collection of facts, such as numbers, words, measurements, observations or just descriptions of things. But data comes in many types, formats and sizes. Understanding what data you will be collecting or working with in a project is important for planning for the management of that data throughout a project.
This seminar will explore data types and help you think about what you need to manage your unique data.
To create reliable and more accurate data, a good understanding of data management terms is important. Get started with data management by understanding the resources, concepts, services, and tools involved throughout the research lifecycle.
This seminar will review key data management terms and jargon used in the field. Learn new terms and ace the RDM Spelling Bee!
Research Data Management (RDM) is essential for responsible research and planning should begin early. Your well-organized and documented data will meet funding agency requirements, be preserved, discoverable and reproducible.
This seminar will review what RDM is, how it applies to your research, and who to contact for assistance.